Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

Preventive Risk-Based Maintenance Scheduling using Discrete-Time Markov Chain Models

Joachim Grimstad1,a, Tamás Ruppert2,c, János Abonyi2,d and Andrey Morozov1,b

1Institute of Automation and software systems, University of Stuttgart, Germany.

2MTA-PE Lendület Complex Systems, Monitoring Research Group, University of Pannonia, Veszprém, Hungary.


The seemingly exponential increase in technological advances and increased globalization forces companies to optimize their maintenance and production activities to remain competitive. This paper proposes a novel Risk-Based Maintenance (RBM) and production decision-making support methodology for manufacturing assets, emphasizing just-in-time manufacturing. The proposed methodology uses historical machine log data to construct a Discrete-Time Markov Chain model (DTMC). The model is then used to evaluate production risk and consider preventive maintenance during the production setup. Probabilistic model checking is applied for the DTMC evaluation. The applicability of the developed method is demonstrated in a real-life case study, where production logs from the semi-automated cutting- and crimping machine are evaluated.

Keywords: Smart manufacturing, Industry 4.0, Risk-based maintenance, Discrete-time Markov chains, Wire harness, Crimping machine.

Download PDF